Visualization and Quantification of the Association Between Breast Cancer and Cholesterol in the All of Us Research Program.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Jianglin Feng, Esteban Astiazaran Symonds, Jason H Karnes
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引用次数: 1

Abstract

Epidemiologic evidence for the association of cholesterol and breast cancer is inconsistent. Several factors may contribute to this inconsistency, including limited sample sizes, confounding effects of antihyperlipidemic treatment, age, and body mass index, and the assumption that the association follows a simple linear function. Here, we aimed to address these factors by combining visualization and quantification a large-scale contemporary electronic health record database (the All of Us Research Program). We find clear visual and quantitative evidence that breast cancer is strongly, positively, and near-linearly associated with total cholesterol and low-density lipoprotein cholesterol, but not associated with triglycerides. The association of breast cancer with high-density lipoprotein cholesterol was non-linear and age dependent. Standardized odds ratios were 2.12 (95% confidence interval 1.9-2.48), P = 5.6 × 10-31 for total cholesterol; 1.99 (1.75-2.26), P = 2.6 × 10-26 for low-density lipoprotein cholesterol; 1.69 (1.3-2.2), P = 9.0 × 10-5 for high-density lipoprotein cholesterol at age < 56; and 0.65 (0.55-0.78), P = 1.2 × 10-6 for high-density lipoprotein cholesterol at age ⩾ 56. The inclusion of the lipid levels measured after antihyperlipidemic treatment in the analysis results in erroneous associations. We demonstrate that the use of the logistic regression without inspecting risk variable linearity and accounting for confounding effects may lead to inconsistent results.

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在我们所有人的研究项目中,乳腺癌和胆固醇之间关系的可视化和量化。
关于胆固醇和乳腺癌之间关系的流行病学证据并不一致。有几个因素可能导致这种不一致,包括有限的样本量、抗高脂血症治疗的混杂效应、年龄和体重指数,以及这种关联遵循简单线性函数的假设。在这里,我们的目标是通过结合可视化和量化大型现代电子健康记录数据库(我们所有人研究计划)来解决这些因素。我们发现清晰的视觉和定量证据表明,乳腺癌与总胆固醇和低密度脂蛋白胆固醇呈强烈、积极和近线性相关,但与甘油三酯无关。乳腺癌与高密度脂蛋白胆固醇的关系是非线性和年龄相关的。总胆固醇的标准化优势比为2.12(95%可信区间为1.9-2.48),P = 5.6 × 10-31;低密度脂蛋白胆固醇1.99 (1.75-2.26),P = 2.6 × 10-26;1.69(1.3-2.2),年龄时高密度脂蛋白胆固醇的P = 9.0 × 10-5,年龄大于或等于56岁时高密度脂蛋白胆固醇的P = 1.2 × 10-6。在分析中纳入抗高脂血症治疗后测量的脂质水平会导致错误的关联。我们证明,使用逻辑回归而不检查风险变量线性和考虑混杂效应可能导致不一致的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cancer Informatics
Cancer Informatics Medicine-Oncology
CiteScore
3.00
自引率
5.00%
发文量
30
审稿时长
8 weeks
期刊介绍: The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
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